library(ggplot2)
library(dplyr)
library(gapminder)
df %>% head()
df %>% nrow()
[1] 234
gapminder %>%
select(year) %>%
unique() %>%
nrow()
[1] 12
gapminder %>%
select(year) %>%
unique() %>%
nrow()
[1] 12
gapminder %>%
group_by(year) %>%
summarize( n=n() )
gapminder %>%
filter (year == "1952") %>%
ggplot (aes ( x= gdpPercap, y= lifeExp)) +
geom_point()

gapminder %>%
filter(gdpPercap>90000, year==1952)
gapminder %>%
filter(country != "Kuwait",year==1952) %>%
ggplot (aes ( x= gdpPercap, y= lifeExp)) +
geom_point()

gapminder %>%
filter(country != "Kuwait",year==1952) %>%
ggplot (aes ( x= gdpPercap, y= lifeExp, color=continent)) +
geom_point()

gapminder %>%
filter(country != "Kuwait",year==1952) %>%
ggplot (aes ( x= gdpPercap, y= lifeExp, color=continent, size= pop)) +
geom_point()

gapminder %>%
filter(country != "Kuwait",year==1952) %>%
ggplot (aes ( x= gdpPercap, y= lifeExp, color=continent, size= pop)) +
geom_point()

gapminder %>%
filter(country != "Kuwait",year==1952) %>%
ggplot (aes ( x= gdpPercap, y= lifeExp, color=continent, size= pop)) +
geom_point(alpha=0.8) +
theme_minimal()

library(plotly)
P<- gapminder %>%
filter(country != "Kuwait",year==1952) %>%
ggplot (aes ( x= gdpPercap, y= lifeExp, color=continent, size= pop)) +
geom_point(alpha=0.8) +
theme_minimal()
ggplotly(P)
data <- read.table("https://raw.githubusercontent.com/holtzy/data_to_viz/master/Example_dataset/1_OneNum.csv", header=TRUE)
df %>% nrow()
[1] 234
df %>% summary()
manufacturer model displ year cyl trans
Length:234 Length:234 Min. :1.600 Min. :1999 Min. :4.000 Length:234
Class :character Class :character 1st Qu.:2.400 1st Qu.:1999 1st Qu.:4.000 Class :character
Mode :character Mode :character Median :3.300 Median :2004 Median :6.000 Mode :character
Mean :3.472 Mean :2004 Mean :5.889
3rd Qu.:4.600 3rd Qu.:2008 3rd Qu.:8.000
Max. :7.000 Max. :2008 Max. :8.000
drv cty hwy fl class
Length:234 Min. : 9.00 Min. :12.00 Length:234 Length:234
Class :character 1st Qu.:14.00 1st Qu.:18.00 Class :character Class :character
Mode :character Median :17.00 Median :24.00 Mode :character Mode :character
Mean :16.86 Mean :23.44
3rd Qu.:19.00 3rd Qu.:27.00
Max. :35.00 Max. :44.00
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